Pregnancy and early life represent crucial windows of susceptibility to environmental exposures, for which epigenomic and metagenomic changes are likely key molecular mediators. We have recently shown in humans and non-human primates that the placental and offspring gut microbiome community and metagenomic function are significantly altered with maternal antenatal (during pregnancy) infection and by the maternal diet. However, the response of the maternal and infant microbiome to highly stressful and microbial laden natural disasters (such as flooding and large-scale population displacement such as recently occurred with Hurricane Harvey) has yet to be studied. Why study the built environmental alongside the maternal and infant microbiome and metabolome in response to Hurricane Harvey? Although it is now established that both microbial laden and anti-microbial exposures render an altered microbiome community in animal models, it is less clear whether this occurs in vivo. Our overarching hypothesis is that during a natural disaster environmental exposures (via inhalation, absorption, and/or ingestion) to atypically encountered microbes (bacteria and fungi) and/or substances with antimicrobial properties will predictably alter the maternal and infant microbiomes. We will specifically test the hypothesis that exposures have a measureable effect only when an absent or dysbiotic/susceptible existing microbial community is present. We propose a series of innovative Aims whereby we will leverage 526 maternal-infant pairs from which maternal samples (placental, vaginal, oral, stool, skin, breastmilk, and nasopharyngeal) and infant specimens (stool, oral, nasopharyngeal, skin) have been collected throughout gestation (first trimester to 8 weeks postpartum) ?pre-Harvey? and compare to those collected ?post-Harvey?. The combined impact of these studies will be to gain mechanistic insight into the contribution of natural disaster environmental exposures on resilient or susceptible maternal and infant microbial communities and their functions, as well as their potential contribution to morbidity, such as PTB and secondary skin and respiratory infections. By integrating exposure measures from our existing, multisite placental, maternal, and infant samples with accompanying robust clinical metadata and existing and derived metagenomics and metabolomics data, we will be able inform and predict attributable risk. After having spent over a decade identifying both exposure risks and molecular mechanisms underlying the developmental origins of disease, we are uniquely poised to rapidly expand and integrate built environment data in our post-Harvey setting in an ongoing cohort with studies which are scientifically rigorous, feasible, justifiable, and of likely long-term significance and high translational impact.